Instructions to use suvadityamuk/TripoSG-diffusers-3d with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use suvadityamuk/TripoSG-diffusers-3d with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("suvadityamuk/TripoSG-diffusers-3d", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
Download model_index.json from suvadityamuk/TripoSG-diffusers-3d: direct link, hf CLI and curl.
- Browser
- Download file 484 Bytes
-
https://huggingface.co/suvadityamuk/TripoSG-diffusers-3d/resolve/main/model_index.json
- Command line
-
hf download hf://suvadityamuk/TripoSG-diffusers-3d/model_index.json
-
curl -L -o model_index.json https://huggingface.co/suvadityamuk/TripoSG-diffusers-3d/resolve/main/model_index.json
484 Bytes
| { | |
| "_class_name": "TripoSGImageTo3DPipeline", | |
| "_diffusers_version": "0.41.0.dev0", | |
| "feature_extractor": [ | |
| "transformers", | |
| "BitImageProcessorPil" | |
| ], | |
| "image_encoder": [ | |
| "transformers", | |
| "Dinov2Model" | |
| ], | |
| "scheduler": [ | |
| "diffusers", | |
| "FlowMatchEulerDiscreteScheduler" | |
| ], | |
| "transformer": [ | |
| "diffusers_3d.families.triposg.models", | |
| "TripoSGTransformerModel" | |
| ], | |
| "vae": [ | |
| "diffusers_3d.families.triposg.vae", | |
| "TripoSGVAEDecoder" | |
| ] | |
| } | |